CN112993337A

CN112993337A - Water management fault diagnosis system suitable for fuel cell attenuation process

Info

Publication number: CN112993337A
Application number: CN201911287113.3A
Authority: CN
Inventors: 邵志刚; 王朋豪; 耿江涛; 何良
Original assignee: Dalian Institute of Chemical Physics of CAS
Current assignee: Dalian Institute of Chemical Physics of CAS
Priority date: 2019-12-14
Filing date: 2019-12-14
Publication date: 2021-06-18
Anticipated expiration: 2039-12-14
Also published as: CN112993337B

Abstract

The invention provides a water management fault diagnosis system for a fuel cell decay process, comprising: a data acquisition unit, which respectively collects the calibration I-V curve of the proton exchange membrane fuel cell under the condition of good wetting and the fuel cell under the real-time working condition The I-V curve data of the The battery internal resistance calibration value R ^* , the battery real-time internal resistance R, the limit current density calibration value J _L ^* and the limit diffusion current density J _L determine the battery fault type, and generate a corresponding fault clearing command; the execution unit, according to the fault clearing Instructions perform fault clearing operations. The present invention eliminates the influence of battery attenuation on model parameters through repeated calibration, does not require additional measurement equipment, reduces costs, and avoids additional failures.

Description

Water management fault diagnosis system suitable for fuel cell attenuation process

Technical Field

The invention relates to the technical field of fuel cells, in particular to a water management fault diagnosis system suitable for a fuel cell attenuation process.

Background

The proton exchange membrane fuel cell has the advantages of high conversion efficiency, cleanness, no pollution, quick start at room temperature and the like, thereby being widely applied to the fields of aerospace, transportation, distributed power generation and the like. However, in the process of commercializing pem fuel cells, cell life and cost have become the focus of increasing attention. The fault diagnosis technology aims to find and remove faults in time by utilizing the state of a galvanic pile monitored in real time so as to improve the durability and stability of the fuel cell. The application of this technology is of great importance to the durability, reliability and maintainability of fuel cell systems.

Common faults in the proton exchange membrane fuel cell include fuel starvation, electrode flooding, membrane dehydration, catalyst poisoning, proton exchange membrane rupture and the like, wherein the flooding and dehydration faults are high in occurrence frequency, recoverable and have great influence on the performance of the fuel cell. Therefore, the research on the water management fault diagnosis method has very important application value. For example, the document (N.Fouquet, et al. journal of Power Sources,2006,159: 905-913.) obtains the model parameters by the method of equivalent circuit fitting, and then diagnoses the flooding and dehydration faults according to the distribution characteristics of the model parameters. Similarly, the literature (c.jeppesen, et al. journal of Power Sources,2017,359: 37-47) employs a data-driven based approach to first extract variable features by collecting electrochemical impedance spectroscopy data, followed by fault identification according to neural network classifiers. Although all the above methods can perform fault diagnosis, the establishment of the equivalent circuit model is full of challenges, and the extra measurement equipment increases the system cost and increases the risk of additional faults. Patent (CN200510126365.X) firstly collects different temperatures and currents under the condition of good wetting of proton exchange membraneThree-dimensional spectrogram R'_ΩF (T, I), and calculating the resistance value R according to the battery voltage change value delta V and the current change value delta I in actual operation_ΩAnd comparing the two values to determine whether water is deficient. The patent (CN201810059712.9) first obtains a hydrogen pressure drop reference value of the stack system under each normal working condition to obtain a regulation control line, collects a current hydrogen side pressure drop, and determines a faulty stack according to the voltage or current of the first stack and the second stack when the current hydrogen side pressure drop is higher than the regulation control line corresponding to the current normal working condition. Although the above fault diagnosis method avoids the use of additional equipment, it has a general disadvantage that it does not consider the influence of battery attenuation on the model parameters (or thresholds), thereby limiting its application.

In the prior art, fault diagnosis is mostly carried out by adopting an equivalent circuit model parameter identification method, but an equivalent circuit model is difficult to obtain, the cost and complexity of a system are increased by additional measuring equipment, and the influence of battery attenuation on model parameters (or threshold values) is generally not considered.

Disclosure of Invention

In view of the defects in the prior art, the invention provides a water management fault diagnosis system suitable for the fuel cell attenuation process, which eliminates the influence of the cell attenuation on model parameters through repeated calibration, does not need additional measuring equipment, reduces the cost and avoids additional faults.

The technical means adopted by the invention are as follows:

a water management fault diagnostic system for a fuel cell decay process, comprising:

the data acquisition unit is used for respectively acquiring calibration I-V curve data of the proton exchange membrane fuel cell under a good wetting condition and I-V curve data of the fuel cell under a real-time working condition;

the calculation unit extracts calibration model parameters according to the calibration I-V curve by a curve fitting method according to the I-V curve model and simultaneously extracts real-time model parameters according to the real-time I-V curve;

a judging unit for calibrating the value R according to the internal resistance of the battery^*The real-time internal resistance R of the battery,Limiting current density calibration value J_L ^*And ultimate diffusion current density J_LJudging the type of the battery fault and generating a fault clearing instruction in response;

the execution unit executes fault clear operation according to the fault clearing instruction;

and the storage unit is used for storing the I-V curve model and the extracted calibration model parameters and real-time model parameters.

Compared with the prior art, the invention has the following advantages:

the invention eliminates the influence of the battery attenuation on the model parameters through repeated calibration, does not need additional measuring equipment, reduces the cost and complexity of the system and avoids additional faults.

For the above reasons, the present invention can be widely applied to the field of fuel cells.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.

FIG. 1 is a block diagram of the system of the present invention.

FIG. 2 is a graph showing the calibration I-V curve and the fitting effect of the PEM fuel cell in example 1.

FIG. 3 is a real-time I-V curve and the fitting effect chart of the PEM fuel cell in example 1.

FIG. 4 is a graph showing a comparison of dehydration failures of the PEM fuel cell in example 1.

FIG. 5 is a graph of the calibration I-V curve and the fitting effect of the PEM fuel cell in example 2.

FIG. 6 is a real-time I-V curve and the fitting effect chart of the PEM fuel cell in example 2.

FIG. 7 is a comparative diagram of the flooding fault of the PEM fuel cell in example 2.

Detailed Description

It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict. The present invention will be described in detail below with reference to the embodiments with reference to the attached drawings. In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

As shown in fig. 1, the present invention provides 1 a water management failure diagnosis system for a fuel cell decay process, including: the device comprises a data acquisition unit, a calculation unit, a judgment unit, an execution unit, a storage unit and a timing unit.

The data acquisition unit is used for respectively acquiring calibration I-V curve data of the proton exchange membrane fuel cell under a good wetting condition and I-V curve data of the fuel cell under a real-time working condition.

And the calculation unit extracts calibration model parameters according to the I-V curve model and the calibration I-V curve by a curve fitting method and simultaneously extracts real-time model parameters according to the real-time I-V curve. The calibration model parameters comprise a battery open-circuit voltage calibration value E₀ ^*Current density calibration value J₀ ^*Limit current density calibration value J_L ^*And battery internal resistance calibration value R^*(ii) a The real-time model parameters comprise real-time internal resistance R and limit diffusion current density J of the battery_L。

Specifically, the I-V curve model is

Wherein, U_aveIs the stack average voltage; u shape_stackIs the total voltage of the stack; n is the number of cells in the stack; e₀Is the single cell open circuit voltage;

is the gas constant; t is the battery temperature; n is the number of electron transfers; α is the electron transfer coefficient; f is the Faraday constant; j is the current density; j is a function of₀Is the exchange current density; r is the internal resistance of the battery; k is the diffusion coefficient; j is a function of_LIs the limiting diffusion current density.

A judging unit for calibrating the value R according to the internal resistance of the battery^*Real-time internal resistance R of battery and limit current density calibration value J_L ^*And ultimate diffusion current density J_LAnd judging the type of the battery fault and generating a fault clearing command in response.

In particular, if (1+ K). R^*<R, wherein K is an interval coefficient and belongs to [0,0.2 ]]Judging that the battery has dehydration fault, and eliminating the fault by increasing the humidity increasing temperature by the execution unit; if (1-K). R^*>R and (1-K). J_L ^*>J_LWherein K is an interval coefficient and belongs to [0,0.2 ]]And judging that the battery has a water logging fault, and at the moment, the execution unit eliminates the fault by increasing the gas metering ratio.

And the timing unit is used for setting a detection cycle period.

The technical solution of the present invention is further explained by the following specific application examples.

Example 1

FIG. 2 is a calibration I-V curve of a PEMFC stack under good wetting conditions and its fitting effect; the proton exchange membrane fuel cell stack consists of 10 single cells, and the single cell membraneThe very effective active area is 270cm²The back pressure is 2bar, and the flow field type is a parallel flow field. The data acquisition conditions of the calibration I-V curve are as follows: the working temperature of the proton exchange membrane fuel cell stack is 60 ℃, the humidity is 60% RH, and the data acquisition range is as follows: 0 to 1.25A cm^-2。

And performing curve fitting on the acquired data according to the I-V curve model, wherein the result is as follows: e₀ ^*＝1.01138V、J₀ ^*＝0.00056Acm²、R^*＝0.13624Ωcm²And J_L ^*＝1.34273Acm²The experimental data and the fitting data are highly consistent, and the fitting model parameters have high reliability.

FIG. 3 is an I-V curve and its fitting effect during real-time operation of a PEMFC stack. The proton exchange membrane fuel cell stack consists of 10 single cells, and the effective active area of the single membrane electrode is 270cm²The back pressure is 2bar, and the flow field type is a parallel flow field. The acquisition conditions of the I-V curve data during real-time work are as follows: the working temperature of the proton exchange membrane fuel cell stack is 60 ℃, the humidity is 0, and the data acquisition range is as follows: 0 to 1.25A cm^-2。

Will calibrate the value E₀ ^*、J_L ^*Substituting the I-V curve data of the pile during real-time operation into an I-V curve model, and obtaining the real-time internal resistance R and the ultimate diffusion current density J of the pile by a curve fitting method_LThe result was 0.15473. omega. cm²、J_L＝1.37230Acm²It can be seen that the experimental data is highly consistent with the fitting data, which shows the real-time internal resistance R and the limiting diffusion current density J of the fitting galvanic pile_LThe reliability is higher.

Comparing the current internal resistance of the battery with the calibrated internal resistance, because (1+ K) · R^*<And R, indicating that the galvanic pile has dehydration failure (K is 0.1). It can be seen from fig. 4 that the method can effectively determine the dehydration failure.

Example 2

FIG. 5 is a calibration I-V curve of a PEMFC under good wetting conditions and its fitting effect; proton exchange membrane fuel cell activityThe area is 50cm²The back pressure is 1bar, and the flow field type is a parallel flow field. The data acquisition conditions of the calibration I-V curve are as follows: the working temperature of the proton exchange membrane fuel cell is 80 ℃, the humidity is 50% RH, and the data acquisition range is as follows: 0.05-1.65A cm^-2。

And performing curve fitting on the acquired data according to the I-V curve model, wherein the result is as follows: e₀ ^*＝0.99957V、J₀ ^*＝0.00096Acm²、R^*＝0.02792Ωcm²And J_L ^*＝1.69612Acm²The experimental data and the fitting data are highly consistent, and the fitting model parameters have high reliability.

Collecting I-V curve data of the galvanic pile during real-time working, wherein the data collection range is as follows: 0.05-1.35A cm^-2. Will calibrate the value E₀ ^*、J_L ^*Substituting the I-V curve data of the pile during real-time operation into an I-V curve model, and obtaining the real-time internal resistance R and the ultimate diffusion current density J of the pile by a curve fitting method_LThe result was 0.00115. omega. cm²、J_L＝1.35213Acm²The fitting effect is shown in fig. 6, and it can be seen that the experimental data is highly consistent with the fitting data, which indicates the real-time internal resistance R and the limiting diffusion current density J of the fitting pile_LThe reliability is higher.

Comparing the current internal resistance of the battery with the calibrated internal resistance because of (1-K). R^*>R and (1-K). J_L ^*>J_LAnd (4) indicating that the galvanic pile has a water flooding fault (K is 0.2). It can be seen from fig. 7 that the method can effectively determine the flooding fault.

Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A water management fault diagnosis system for fuel cell decay process, characterized in that, comprising:

The data acquisition unit collects the calibration I-V curve data of the proton exchange membrane fuel cell under the condition of good wetting and the I-V curve data of the fuel cell under the real-time working condition;

The calculation unit, according to the I-V curve model, extracts the calibration model parameters according to the calibration I-V curve by the method of curve fitting, and simultaneously extracts the real-time model parameters according to the real-time I-V curve;

The judgment unit judges the battery fault type according to the battery internal resistance calibration value R ^* , the battery real-time internal resistance R, the limit current density calibration value J _L ^* and the limit diffusion current density J _L , and generates a corresponding fault clearing command;

an execution unit, performing a fault clearing operation according to the fault clearing instruction;

The storage unit stores the I-V curve model and the extracted calibration model parameters and real-time model parameters.

2 . The water management fault diagnosis system for a fuel cell decay process according to claim 1 , wherein the calibration model parameters include a battery open circuit voltage calibration value E ₀ ^* , a current density calibration value J ₀ ^* , a limit The current density calibration value J _L ^* and the battery internal resistance calibration value R ^* ; the real-time model parameters include the battery real-time internal resistance R and the limiting diffusion current density J _L .

3. The water management fault diagnosis system for fuel cell decay process according to claim 1 or 2, characterized in that, the system further comprises a timing unit for setting a detection cycle period.

4. The water management fault diagnosis system for fuel cell decay process according to claim 1, wherein the I-V curve model is

Among them, U _ave is the average voltage of the stack; U _stack is the total voltage of the stack; N is the number of cells in the stack; E ₀ is the open-circuit voltage of a single cell;

is the gas constant; T is the cell temperature; n is the number of electrons transferred; α is the electron transfer coefficient; F is the Faraday constant; j is the current density; j ₀ is the exchange current density; R is the cell internal resistance; k is the diffusion coefficient; j _L is the limiting diffusion current density.

5 . The water management fault diagnosis system for a fuel cell decay process according to claim 1 , wherein the judging unit for judging the fault type comprises: 6 .

If (1+K)·R ^* <R, where K is the interval coefficient, and K∈[0,0.2], it is judged that the battery has a dehydration failure. At this time, the execution unit eliminates the failure by increasing the humidification temperature;

If (1-K)·R ^* >R and (1-K)·J _L ^* >J _L , where K is the interval coefficient, and K∈[0,0.2], then it is judged that the battery has a flooded fault, at this time , the execution unit eliminates the fault by increasing the gas metering ratio.